Add repository card

README.md

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+---
+license: apache-2.0
+task_categories:
+  - text-generation
+language:
+  - en
+tags:
+  - multi-agent
+  - supervised-fine-tuning
+  - information-retrieval
+  - question-answering
+pretty_name: WideSeek-R1 SFT Data
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: sft_width_depth_agent_1p3.jsonl
+---
+
+# WideSeek-R1 SFT Data
+
+This dataset contains agent-level, multi-turn supervised fine-tuning trajectories for both width-only and depth-only tasks in WideSeek-R1.
+
+## Construction
+
+The trajectories were generated by [Qwen3-235B-A22B](https://huggingface.co/Qwen/Qwen3-235B-A22B) using the WideSeek-R1 multi-agent workflow with offline retrieval tools. Width and depth trajectories are balanced at the question level.
+
+For each question-level trajectory, we retain one main-agent session and up to three subagent sessions, giving a target main-to-subagent ratio of 1:3. If fewer than three valid subagents are available, all available subagents are retained. When more than three are available, representative sessions are selected according to their turn lengths.
+
+Each JSONL row represents one complete agent session and may contain multiple assistant turns. The dataset includes 1,903 width trajectories and 1,903 depth trajectories.
+
+## Format
+
+Each row contains:
+
+- `messages`: the complete multi-turn message history for one agent;
+- `tools`: the tool definitions available to that agent;
+- `metadata`: the task type, agent role, trajectory identifiers, and related information.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("WideSeek-R1/WideSeek-R1-SFT-data")
+```